Retrieval Augmented Generation with LlamaIndex
Master Retrieval Augmented Generation with LlamaIndex
Discover how to build smart document-based chat applications by combining retrieval techniques with language models using LlamaIndex. You will learn to manage embeddings, handle metadata, and improve response quality through summarization and index management. Gain hands-on experience implementing Retrieval Augmented Generation workflows.
Packt | May 2026 | 61 min
What You Will Learn
You will start by exploring the core ideas behind Retrieval Augmented Generation and see how retrieval supports language models. Through step-by-step exercises, you will set up your environment, create document chat systems, manage embeddings, and apply summarization. Each topic is reinforced with practical tasks to help you apply new skills right away.
Key Features
- Build document-based chat apps that deliver accurate, context-aware responses
- Manage embeddings, document metadata, and indexes for efficient retrieval
- Customize language models and use summarization to enhance generated outputs
Target Audience
Designed for AI developers, data engineers, and NLP enthusiasts who want to create advanced chatbots or knowledge retrieval tools. If you have a basic understanding of Python and some experience with language models, you will be able to follow along and put these techniques into practice.
